Health management is a modern phrase for equipment condition monitoring and maintenance planning, especially in an asset-intensive and downtime-sensitive industry. In a historical perspective, Condition Monitoring System (CMS) is a generally accepted term for a ground-based (remote) or an on-board system (local) that performs some level of condition monitoring and health management. The scope of a CMS typically includes fault alert, detection, and isolation. Maintenance planning is performed by some ground-based systems and is mostly concerned with scheduled inspections and time-based repairs, or On-Condition Maintenance (OCM), i.e., a part is replaced only for cause.
With the recently emphasis on Reliability-Centered Maintenance (RCM), the goal of health management has been focused on implementing a systematic process of determining the maintenance requirements of a physical asset, which may be an entire piece of equipment such as an engine or a single part of the equipment/system, to ensure its readiness, performance, and operability. To determine maintenance requirements effectively, the identification of potential failures and the prediction of failure progressions are essential; hence the Condition Based Maintenance (CBM) or Prognostics and Health Management (PHM) philosophy has also been emphasized recently in industries such as the aerospace industry. The various functions of health management are illustrated in FIG. 1.
The purpose of equipment health management is to realize significant benefits in operations planning and reduced cost of ownership. To realize these benefits, the various health management functions, as illustrated in FIG. 1, must be efficiently integrated and timely updated with new information. Many monitoring techniques exist to address CBM or RCM requirements; however, most of these techniques focus on a specific monitoring application, or they try to solve a particular problem in equipment health management. Furthermore, some of these techniques suffer from frequent false alarms (or false detections) because the nature of the data is noisy and complex which do not lend themselves for traditional statistical or data-centric analysis
Thus, there is an increasing need for improved machinery and/or equipment health management and methods for meeting the accuracy and system integration requirements of modern condition monitoring practices like the CBM and RCM. This need for effective monitoring of machinery/condition and efficient maintenance planning is present not just for the aerospace industry, it is prevalent for other industries as well, including, but not limited to transportation, industrial production, and manufacturing.